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JAMES O. MCINERNEY James.Mcinerney at UCG.IE
Fri Aug 25 03:49:48 EST 1995

>In article <41hlip$du1 at mserv1.dl.ac.uk> Javier Quintero Vazquez <bnjquint at usc.es> writes:
>>Can anyone tell me:
>>a.-In your opinion, the transition/transversion rate that would be used 
>>in DNADIST program to the Cytochrome B sequence of fishes.
>Ummm..... in the first place I would argue that you should not use distances 
>as they violate triangle inequalities and assume constancy.  Second, 
>estimates of TV:TS are usually between 1:2 and 1:10 I think.  If you
>don't have a good way of telling... do you really think you should just pull a 
>ratio out of the sky?
>>b.-Previously, can I expect many differences between: a tree building with
>>distances based methods/a tree building with parsimony/cladistic methods.
>The distance-generated tree will have _no_ logical basis, whereas
>the parsimony-generated tree will have.  In the distance tree you will not
>be able to reconstruct evolutionary changes whereas in the parsimony
>tree you will.

Well, we haven't had this kind of answer on this group for a while.  I know
that prejudices do exist and some people prefer parsimony methods and some
people prefer distance based methods.  However I feel that when somebody
asks a question in this way that they should receive the pros and cons of

Briefly, the argument against parsimony is that the first thing you do is take
the majority of the characters in your data set and throw them out.  Also there
is no statistical framework built into the parsimony procedure, so should you
accept the most parsimonious tree as the one and only, with no idea of how good
or bad this tree really is (what about multiple equally parsimonious trees?)?

The argument against distance based methods (in addition to the ones mentioned
above by M. Siddall) is that you use some characters in a negative way (an
analogy: mushrooms, E. coli and the oak tree are joined together by virtue of
not possessing vertebrae), with cladistic methods, organisms are put together
only if they share characters that have arisen relatively recently
(shared-derived characters).

Now for my humble opinion...A distance method can be very good (as we see from
simulation studies) at retrieving the correct tree, especially if one chooses
the proper correction for multiple hits.  When a good tree building method like
the neighbor joining method is used then the chances of retrieving the correct
tree are pretty o.k.

Parsimony is really neat for examining how evolution has occurred, which
characters are leading to confusion and instability, what is the general mode
of evolution (transformation from one character state to another).

The philosophy of the investigator is personal, but as a bench scientist who
cares more about the result and the hypotheses I can make from my data than
any philosophical do's and don'ts, my advice is to use both.  Agreement is good,
anywhere there is no agreement is probably a weakly supported part of the tree
anyway.  In fact if you look at the literature, most scientists will use both


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